MCP: Build Agents with Claude, Cursor, Flowise, Python & n8n
MCP: Xây dựng AI Agent với Claude, Cursor, Flowise, Python & n8n
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The Model Context Protocol (MCP) is one of the most exciting new technologies in AI automation and agent development.
Because Large Language Models need more than just prompts — they need context, tools, and external resources.
With MCP, you can provide exactly that.
But how does it work in practice?
How do you build your own MCP servers?
How do you use clients like Claude Desktop, Cursor, Windsurf, n8n or Flowise?
And how can you automate, secure, and integrate it all into your own AI project?
In this course, you'll learn exactly that – step by step, clearly explained, with many examples and ready-to-use workflows.
Fundamentals: Understand and Use the Model Context Protocol
Get a comprehensive overview of the MCP concept, how it works, and where to apply it
Learn how tools, prompts, and resources can be connected to LLMs like Claude, GPT, or Gemini using MCP
Start with practical tips, materials, and a dedicated course hub full of resources and curated references
Understand the key principles of prompt engineering and how system prompts work in the MCP context
Integrate MCP in Claude Desktop & Set Up Your First Servers
Install Claude Desktop using Node.js and NVM and configure your first server structures
Use JSON files and the official MCP installer to connect tools, databases, or your own APIs
Understand different server types (tool servers, prompt servers, database MCPs) and their use cases
Connect Claude Desktop with your local system or online services and enable API key–protected access
Install Python using pyenv and set up the UV package manager for running your first local MCP server
Combine MCP with Cursor, Vibe Coding & Python
Set up Cursor as a flexible client, connect it to existing MCP servers (e.g., Zapier), and explore its limitations and strengths
Use Vibe Coding and Python-based configurations to customize your MCP structure
Manage API keys efficiently, understand pricing structures, and build your own cross-tool MCP setup
Create, Host & Automate MCP Servers with n8n
Learn how to install and configure n8n locally and use it as a full-featured MCP platform
Create triggers and actions, and use custom nodes to connect Claude, Cursor, GitHub, or Google Drive
Integrate Pinecone and other vector databases for RAG agents directly into your MCP server
Learn how to host MCP servers on a VPS and keep them running 24/7 with secure access
Use authentication options and GDPR-compliant hosting strategies for secure deployments
Use MCP in Flowise, LangChain & LangGraph
Install Flowise and build complex tool workflows (email, calendar, Airtable, web search) using Agent V2
Use LangGraph to manage multi-step agent processes with clear role separation and tool execution
Manage Pinecone databases via SQLite, combine LangChain functionality, and build scalable automations
Explore the Flowise interface and create your own assistants with full MCP integration
Creative Projects & Specialized Workflows with MCP
Build voice interfaces for your LLM and control your AI through speech input using MCP
Automate 3D workflows in Blender with Claude, Python, and your own MCP server
Use the OpenAI API with n8n to generate images automatically
Share ideas with the community and explore creative or unconventional use cases
Develop Your Own MCP Servers in Python
Learn how to write MCP servers using Python and TypeScript – including prompt handling, tool integration, and resources
Use the modelcontextprotocol Python SDK to develop your own Claude-compatible prompt templates
Use the MCP Inspector for debugging and diagnostics, and expand your setup with Server-Sent Events (SSE)
Understand all transport types for MCP: STDIO, SSE, and Streamable HTTP – when and how to use them
Publish your MCP server on GitHub and explore hosting options like Cloudflare, AWS, or Azure
Avoid common mistakes and apply best practices for stable, secure server development
Security, Privacy & Legal Foundations
Recognize and understand threats like tool poisoning, jailbreaks, prompt injections, and MCP rug pulls
Secure your MCP server with API keys, authentication, and proper access control
Understand key data privacy regulations like GDPR and the EU AI Act, and address the challenges of hosting generative AI
Learn from real-world examples and get clear guidance on how to stay legally and technically compliant
After the course…
You will be able to build, host, develop, and integrate MCP-based agents into tools like Claude, n8n, Cursor, or Flowise.
You will know how to create secure MCP servers, combine them for your own projects, and even offer them as a service.
Whether for business or personal ideas – this course gives you full control over the MCP ecosystem.
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